SIMCOAL 2.0: a program to simulate genomic diversity over large recombining regions in a subdivided population with a complex history

We present an extension of the program SIMCOAL, which allows for simulation of the genomic diversity of samples drawn from a set of populations with arbitrary patterns of migrations and complex demographic histories, including bottlenecks and various modes of demographic expansion. The main additions to the previous version include the possibility of arbitrary and heterogeneous recombination rates between adjacent loci and multiple coalescent events per generation, allowing for the simulation of very large samples and recombining genomic regions, together with the simulation of single nucleotide polymorphism data with frequency ascertainment bias. AVAILABILITY: http://cmpg.unibe.ch/software/simcoal2/.     

Sequence-level population simulations over large genomic regions

Simulation is an invaluable tool for investigating the effects of various population genetics modeling assumptions on resulting patterns of genetic diversity, and for assessing the performance of statistical techniques, for example those designed to detect and measure the genomic effects of selection. It is also used to investigate the effectiveness of various design options for genetic association studies. Backward-in-time simulation methods are computationally efficient and have become widely used since their introduction in the 1980s. The forward-in-time approach has substantial advantages in terms of accuracy and modeling flexibility, but at greater computational cost. We have developed flexible and efficient simulation software and a rescaling technique to aid computational efficiency that together allow the simulation of sequence-level data over large genomic regions in entire diploid populations under various scenarios for demography, mutation, selection, and recombination, the latter including hotspots and gene conversion. Our forward evolution of genomic regions (FREGENE) software is freely available from www.ebi.ac.uk/projects/BARGEN together with an ancillary program to generate phenotype labels, either binary or quantitative. In this article we discuss limitations of coalescent-based simulation, introduce the rescaling technique that makes large-scale forward-in-time simulation feasible, and demonstrate the utility of various features of FREGENE, many not previously available.     

Simulating a base population in honey bee for molecular genetic studies

Background

Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (Varroa destructor) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee.

Results

Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ² statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r² values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r² value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency.

Conclusion

We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html     

Critical assessment of coalescent simulators in modeling recombination hotspots in genomic sequences

Background

Coalescent simulation is pivotal for understanding population evolutionary models and demographic histories, as well as for developing novel analytical methods for genetic association studies for DNA sequence data. A plethora of coalescent simulators are developed, but selecting the most appropriate program remains challenging.

Results

We extensively compared performances of five widely used coalescent simulators – Hudson’s ms, msHOT, MaCS, Simcoal2, and fastsimcoal, to provide a practical guide considering three crucial factors, 1) speed, 2) scalability and 3) recombination hotspot position and intensity accuracy. Although ms represents a popular standard coalescent simulator, it lacks the ability to simulate sequences with recombination hotspots. An extended program msHOT has compensated for the deficiency of ms by incorporating recombination hotspots and gene conversion events at arbitrarily chosen locations and intensities, but remains limited in simulating long stretches of DNA sequences. Simcoal2, based on a discrete generation-by-generation approach, could simulate more complex demographic scenarios, but runs comparatively slow. MaCS and fastsimcoal, both built on fast, modified sequential Markov coalescent algorithms to approximate standard coalescent, are much more efficient whilst keeping salient features of msHOT and Simcoal2, respectively. Our simulations demonstrate that they are more advantageous over other programs for a spectrum of evolutionary models. To validate recombination hotspots, LDhat 2.2 rhomap package, sequenceLDhot and Haploview were compared for hotspot detection, and sequenceLDhot exhibited the best performance based on both real and simulated data.

Conclusions

While ms remains an excellent choice for general coalescent simulations of DNA sequences, MaCS and fastsimcoal are much more scalable and flexible in simulating a variety of demographic events under different recombination hotspot models. Furthermore, sequenceLDhot appears to give the most optimal performance in detecting and validating cross-over hotspots.     

GIST: Genomic island suite of tools for predicting genomic islands in genomic sequences

Genomic Islands (GIs) are genomic regions that are originally from other organisms, through a process known as Horizontal Gene Transfer (HGT). Detection of GIs plays a significant role in biomedical research since such align genomic regions usually contain important features, such as pathogenic genes. We have developed a use friendly graphic user interface, Genomic Island Suite of Tools (GIST), which is a platform for scientific users to predict GIs. This software package includes five commonly used tools, AlienHunter, IslandPath, Colombo SIGI-HMM, INDeGenIUS and Pai-Ida. It also includes an optimization program EGID that ensembles the result of existing tools for more accurate prediction. The tools in GIST can be used either separately or sequentially. GIST also includes a downloadable feature that facilitates collecting the input genomes automatically from the FTP server of the National Center for Biotechnology Information (NCBI). GIST was implemented in Java, and was compiled and executed on Linux/Unix operating systems. AVAILABILITY: The database is available for free at http://www5.esu.edu/cpsc/bioinfo/software/GIST.     

Recombination-filtered genomic datasets by information maximization

With the increasing amount of DNA sequence data available from natural populations, new computational methods are needed to efficiently process raw sequences into formats that are applicable to a variety of analytical methods. One highly successful approach to inferring aspects of demographic history is grounded in coalescent theory. Many of these methods restrict themselves to perfectly tree-like genealogies (i.e. regions with no observed recombination), because theoretical difficulties prevent ready statistical evaluation of recombining regions. However, determining which recombination-filtered dataset to analyze from a larger recombination-rich genomic region is a non-trivial problem. Current applications primarily aim to quantify recombination rates (rather than produce optimal recombination-filtered blocks), require significant manual intervention, and are impractical for multiple genomic datasets in high-throughput, automated research environments. Here, we present a fast, simple and automatable command-line program that extracts optimal recombination-filtered blocks (no four-gamete violations) from recombination-rich genomic re-sequence data. Availability: http://hammerlab.biosci.arizona.edu/software.html.     

Identifying multiple alignment regions satisfying simple formulas and patterns

MOTIVATION: When studying multiple alignments of genomic sequences one frequently aims to locate and count regions which satisfy a set of constraints. These regions may be putatively functional, but researchers may also be interested in quantifying the frequency of occurrences of certain patterns. RESULTS: We have developed a program that applies simple formulas and pattern specifications to multiple alignments, reporting the positions and counts of conforming regions. As an example, we have navigated a 15-species alignment of the CAV2-CAV1 region and outlined some findings regarding PPARgamma binding sites. AVAILABILITY: Our software and the accompanying documentation can be obtained at no charge by contacting the authors. It can also be accessed at http://ranger.uta.edu/~nick/compgen     

SNPbox: a modular software package for large-scale primer design

SUMMARY: We developed a modular software package SNPbox that automates and standardizes the generation of PCR primers and is used in the strategy for constructing single nucleotide polymorphisms (SNPs) maps. In this strategy, the focus of primer design can be either on the validation of annotated public SNPs or on the SNP discovery in exon regions or extended genomic regions, both by resequencing. SNPbox relies on Primer3 for the primer design and combines this program with other publicly available software tools such as BLAST, Spidey and RepeatMasker, and newly developed algorithms. Primer conditions were chosen such that PCR amplifications are uniform for each PCR amplicon facilitating the use of high-throughput genetic platforms. SNPbox can also be used for the design of primer sets for mutation analysis, STR marker genotyping and microarray oligo design. Of the 2500 primer sets designed by SNPbox, 95% successfully amplified genomic DNA under uniform PCR conditions. AVAILABILITY: The software is available from the authors upon request. SUPPLEMENTARY INFORMATION: SNPbox_supplement.     

MAP2: multiple alignment of syntenic genomic sequences

We describe a multiple alignment program named MAP2 based on a generalized pairwise global alignment algorithm for handling long, different intergenic and intragenic regions in genomic sequences. The MAP2 program produces an ordered list of local multiple alignments of similar regions among sequences, where different regions between local alignments are indicated by reporting only similar regions. We propose two similarity measures for the evaluation of the performance of MAP2 and existing multiple alignment programs. Experimental results produced by MAP2 on four real sets of orthologous genomic sequences show that MAP2 rarely missed a block of transitively similar regions and that MAP2 never produced a block of regions that are not transitively similar. Experimental results by MAP2 on six simulated data sets show that MAP2 found the boundaries between similar and different regions precisely. This feature is useful for finding conserved functional elements in genomic sequences. The MAP2 program is freely available in source code form at http://bioinformatics.iastate.edu/aat/sas.html for academic use.     

BACFinder: genomic localisation of large insert genomic clones based on restriction fingerprinting

We have developed software that allows the prediction of the genomic location of a bacterial artificial chromosome (BAC) clone, or other large genomic clone, based on a simple restriction digest of the BAC. The mapping is performed by comparing the experimentally derived restriction digest of the BAC DNA with a virtual restriction digest of the whole genome sequence. Our trials indicate that this program identified the genomic regions represented by BAC clones with a degree of accuracy comparable to that of end-sequencing, but at considerably less cost. Although the program has been developed principally for use with Arabidopsis BACs, it should align large insert genomic clones to any fully sequenced genome.     

A flexible forward simulator for populations subject to selection and demography

This article introduces a new forward population genetic simulation program that can efficiently generate samples from populations with complex demographic histories under various models of natural selection. The program (SFS_CODE) is highly flexible, allowing the user to simulate realistic genomic regions with several loci evolving according to a variety of mutation models (from simple to context-dependent), and allows for insertions and deletions. Each locus can be annotated as either coding or non-coding, sex-linked or autosomal, selected or neutral, and have an arbitrary linkage structure (from completely linked to independent). AVAILABILITY: The source code (written in the C programming language) is available at http://sfscode.sourceforge.net, and a web server (http://cbsuapps.tc.cornell.edu/sfscode.aspx) allows the user to perform simulations using the high-performance computing cluster hosted by the Cornell University Computational Biology Service Unit.     

BLAST2GENE: a comprehensive conversion of BLAST output into independent genes and gene fragments

SUMMARY: BLAST2GENE is a program that allows a detailed analysis of genomic regions containing completely or partially duplicated genes. From a BLAST (or BL2SEQ) comparison of a protein or nucleotide query sequence with any genomic region of interest, BLAST2GENE processes all high scoring pairwise alignments (HSPs) and provides the disposition of all independent copies along the genomic fragment. The results are provided in text and PostScript formats to allow an automatic and visual evaluation of the respective region. AVAILABILITY: The program is available upon request from the authors. A web server of BLAST2GENE is maintained at http://www.bork.embl.de/blast2gene     

EGID: an ensemble algorithm for improved genomic island detection in genomic sequences

Genomic islands (GIs) are genomic regions that are originally transferred from other organisms. The detection of genomic islands in genomes can lead to many applications in industrial, medical and environmental contexts. Existing computational tools for GI detection suffer either low recall or low precision, thus leaving the room for improvement. In this paper, we report the development of our Ensemble algorithm for Genomic Island Detection (EGID). EGID utilizes the prediction results of existing computational tools, filters and generates consensus prediction results. Performance comparisons between our ensemble algorithm and existing programs have shown that our ensemble algorithm is better than any other program. EGID was implemented in Java, and was compiled and executed on Linux operating systems. EGID is freely available at http://www5.esu.edu/cpsc/bioinfo/software/EGID.     

JContextExplorer: a tree-based approach to facilitate cross-species genomic context comparison

Background

Cross-species comparisons of gene neighborhoods (also called genomic contexts) in microbes may provide insight into determining functionally related or co-regulated sets of genes, suggest annotations of previously un-annotated genes, and help to identify horizontal gene transfer events across microbial species. Existing tools to investigate genomic contexts, however, lack features for dynamically comparing and exploring genomic regions from multiple species. As DNA sequencing technologies improve and the number of whole sequenced microbial genomes increases, a user-friendly genome context comparison platform designed for use by a broad range of users promises to satisfy a growing need in the biological community.

Results

Here we present JContextExplorer: a tool that organizes genomic contexts into branching diagrams. We implement several alternative context-comparison and tree rendering algorithms, and allow for easy transitioning between different clustering algorithms. To facilitate genomic context analysis, our tool implements GUI features, such as text search filtering, point-and-click interrogation of individual contexts, and genomic visualization via a multi-genome browser. We demonstrate a use case of our tool by attempting to resolve annotation ambiguities between two highly homologous yet functionally distinct genes in a set of 22 alpha and gamma proteobacteria.

Conclusions

JContextExplorer should enable a broad range of users to analyze and explore genomic contexts. The program has been tested on Windows, Mac, and Linux operating systems, and is implemented both as an executable JAR file and java WebStart. Program executables, source code, and documentation is available at http://www.bme.ucdavis.edu/facciotti/resources_data/software/.     

Combining functional and linkage disequilibrium information in the selection of tag SNPs

We have developed an online program, WCLUSTAG, for tag SNP selection that allows the user to specify variable tagging thresholds for different SNPs. Tag SNPs are selected such that a SNP with user-specified tagging threshold C will have a minimum R2 of C with at least one tag SNP. This flexible feature is useful for researchers who wish to prioritize genomic regions or SNPs in an association study. AVAILABILITY: The online WCLUSTAG program is available at http://bioinfo.hku.hk/wclustag/     

In silico Biochemical Reaction Network Analysis (IBRENA): a package for simulation and analysis of reaction networks

Summary: We present In silico Biochemical Reaction Network Analysis(IBRENA), a software package which facilitates multiple functionsincluding cellular reaction network simulation and sensitivityanalysis (both forward and adjoint methods), coupled with principalcomponent analysis, singular-value decomposition and model reduction.The software features a graphical user interface that aids simulationand plotting of in silico results. While the primary focus isto aid formulation, testing and reduction of theoretical biochemicalreaction networks, the program can also be used for analysisof high-throughput genomic and proteomic data. Availability: The software package, manual and examples areavailable at http://www.eng.buffalo.edu/~neel/ibrena Contact: neel{at}eng.buffalo.edu Associate Editor: Limsoon Wong     

UniPrime: a workflow-based platform for improved universal primer design

UniPrime is an open-source software (http://uniprime.batlab.eu), which automatically designs large sets of universal primers by simply inputting a gene ID reference. UniPrime automatically retrieves and aligns homologous sequences from GenBank, identifies regions of conservation within the alignment and generates suitable primers that can amplify variable genomic regions. UniPrime differs from previous automatic primer design programs in that all steps of primer design are automated, saved and are phylogenetically limited. We have experimentally verified the efficiency and success of this program by amplifying and sequencing four diverse genes (AOF2, EFEMP1, LRP6 and OAZ1) across multiple Orders of mammals. UniPrime is an experimentally validated, fully automated program that generates successful cross-species primers that take into account the biological aspects of the PCR.